"To let learn". Between philosohy and didactics of philosophy in high school
Bibliographic record
Abstract
I develop here a hermeneutical reflection on some issues around the teaching of philosophy in high school in Colombia. Following the Hermeneutics school in Alberta, Canada, I develop interpretation based on real experiences, etymologies, metaphors and frequent connections with personal life in order to deepen the phenomenon addressed (not to find or reveal its truth). In this way, I opt for a less scientific and formal language that aims to propose proven and definitive knowledge. I thus highlight the reflective side of the document. Regarding the theme or phenomenon, this text focuses on a prejudice that probably persists strongly among philosophy teachers in Colombia and that allows us to understand why it is and has been so difficult to change the ways of teaching philosophy: the teacher He is the one who must teach and the student learn. I offer here my interpretation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.031 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".